Lyon y Maxwell 2007

7/28/2019 Lyon y Maxwell 2007

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Greenwash: Corporate Environmental

Disclosure under Threat of Audit

Thomas P. Lyonand John W. Maxwell

August 8, 2005

Abstract

We develop an economic model of greenwash, in which a firm strate-

gically discloses environmental information and a non-governmental orga-nization (NGO) may audit and penalize the firm for engaging in green-wash. We identify conditions under which NGO punishment of greenwashbackfires, inducing the firm to become less rather than more forthcomingabout its environmental performance. We show that complementaritieswith NGO auditing may justify public policies encouraging firms to adoptenvironmental management systems. Mandatory disclosure rules offerthe potential for better performance than NGO auditing, but the neces-sary penalties may be so large as to be p olitically unpalatable. If so,a mix of mandatory disclosure rules, NGO auditing and environmental

management systems may be needed.

1 Introduction

Environmental issues have been on the corporate radar screen for years. Thou-sands offirms participate in the Environmental Protection Agencys partnershipprograms, and many more participate in industry-led environmental programs

such as the Council of Great Lakes Industries or the American Chemistry Coun-cils Responsible Care program.1 Despite these efforts, large portions of thepublic continue to view business as an enemy of the environment. Furthermore,although companies naturally want to publicize their environmentally-friendlyactions, firms are often surprisingly hesitant to promote their environmentalsuccesses or to issue detailed environmental reports. Indeed, based on his inter-views with managers in charge of corporate social responsibility, Peloza (2005)


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finds that Many managers worry that by overtly promoting their participationstakeholders might view the activity as self-serving. In fact, many respondentsreported minimal or no attempts of self-promotion. For example, one of hissurvey respondents commented that Were pretty sensitive. We dont want togo out thumping our chests saying oh, arent we wonderful and heres all thegreat things we do! We want people to see for themselves and they can drawtheir own conclusions.2

Despite the increase in corporate environmental activity, many such actionsare dismissed as mere greenwash by non-governmental organizations. Un-fortunately, public debate around greenwash is often both vague and strident.For example, in Greenwash: The Reality Behind Corporate Environmentalism,Greenpeace activists Jed Greer and Kenny Bruno excoriate twenty leading firmsthat proclaim their environmentalism for failing to take actions strong enoughto justify their public proclamations. For example, they note that Shell Oil ac-knowledges publicly that global climate change poses a great enough risk to

justify starting to adopt precautionary measures. Yet despite this ostensible

commitment to a precautionary approach, Shell plays an aggressive role in thedrive to develop the worlds one trillion barrels of known oil reserves... 3 Ex-actly what Shell would have to do to avoid being labeled a greenwasher isunclear.

The activists criticizing firms like Shell and BP are undoubtedly trying topress these firms to improve their environmental performance. Nevertheless,if companies fear being publicly smeared for their environmental initiatives,this outcome may not be achieved. Unfortunately, popular usage of the termgreenwash" tends to be both strident and vague. For example, in their book on

greenwash, Greer and Bruno (1996) never actually define the term. On the firstpage of the Introduction, however, they describe the world of greenwash as one inwhich transnational corporations are preserving and expanding their marketsby posing as friends of the environment and leaders in the struggle to eradicatepoverty. The implication is clearly that companies are misrepresenting theirenvironmental performance. However, a deeper analysis suggests that firmsenvironmental claims are typically not false, although they often fail to presentthe full picture. It turns out this distinction has important implications for theeffectiveness of NGO campaigns against greenwashers, and also suggests some

novel public policy measures.In this paper, we present what is to our knowledge the first economic analy-

sis of greenwash. Since public discussion of greenwash is often polemical andimprecise, we begin in section 2 by developing a clear formal definition of green-wash, and distinguishing it from other disinformation strategies. In section3, we build a simple model in which a firm makes strategic decisions about theenvironmental information it discloses publicly, and a non-governmental orga-


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model allows us to study rigorously in section 4 how such NGO tactics affectthe firms incentives, and to assess whether such NGO actions actually improvemarket performance. We identify a set of conditions under which NGO pun-ishment of greenwash backfires, inducing the firm to become less rather thanmore forthcoming about its environmental performance. We find this is par-ticularly likely for firms in relatively clean industries that are not well informedabout their own environmental impacts. We then consider potential comple-

mentarities between NGO auditing of greenwash and corporate adoption of anenvironmental management system (EMS), and show that these complementar-ities may justify public policies encouraging firms to adopt EMSs. Our analysispoints to a new rationale for encouraging firms to adopt EMSs:.with an EMS inplace, the firm is more likely to be well informed about its own environmentalimpact, and more importantly, the market knows that thefirm is more likely tobe well informed. As a result, NGO auditing is less likely to backfire, and thefirm is more likely to fully disclose under threat of audit. In section 5, we studythe effects of mandatory disclosure rules (such as those created by the Public

Company Accounting and Reform Act of 2002, commonly know as Sarbanes-Oxley). We show that mandatory disclosure rules offer the potential for betterperformance than NGO auditing, but that the necessary penalties may be solarge as to be politically unpalatable. Finally, we consider the interaction be-tween mandatory disclosure rules, NGO auditing, and the adoption of EMSs,and offer some tentative suggestions regarding how these mechanisms can bestbe combined. Section 6 concludes.

2 Defining GreenwashFormal analysis of greenwash must begin with a clear definition of the phenom-enon. Unfortunately, popular usage of the term, and even academic discussionof it, tends to be broad and vague. In their book on greenwash, Greer and Bruno(1996) never actually define the term. On the first page of the Introduction,however, they describe the world of greenwash as one in which transnationalcorporations are preserving and expanding their markets by posing as friendsof the environment and leaders in the struggle to eradicate poverty. Even

academic discussions can be broad. Laufer (2003), for example, presents a setof elements of greenwashing that include confusion, fronting, and postur-ing. Confusion (p. 257) is achieved through careful document control andstrict limits on the flow of information made available to regulators and prose-cutors. Fronting (p. 257) is realized by subordinate scapegoating or reversewhistle blowing, and may involve actions such as cast doubt on the severityof the problem or emphasize uncertainty associated with problem. Posturing


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Turning to the dictionary, we find that Websters New Millenium Dictionaryof English defines greenwash as The practice of promoting environmentallyfriendly programs to deflect attention from an organizations environmentallyunfriendly or less savory activities." The Concise Oxford English Dictionary(10th Edition) defines it as: Disinformation disseminated by an organizationso as to present an environmentally responsible public image; a public image ofenvironmental responsibility promulgated by or for an organization etc. but per-

ceived as being unfounded or intentionally misleading. Both these definitionsemphasize the idea that the public has limited information about corporate en-vironmental performance, and that corporations therefore can manipulate thedissemination of information to mislead the public. These ideas are consistentwith what Laufer refers to as confusion.

The term disinformation goes somewhat further, and implies the provisionof deliberately false or fraudulent messages. Corporate greenwashing, however,does not seem to fit this definition. Instead, the typical concerns raised byNGOs are that companies present positive information out of context in a way

that could be misleading to individuals who lack background information aboutthe companys full portfolio of activities. Consider the following example, takenfrom Dont Be Fooled: The Ten Worst Greenwashers of 2003:4

Royal Caribbean points to its advanced wastewater treatment sys-tems as a sign of environmental progressiveness, yet they are in-stalled on just 3 of the companys 26 cruise ships. The advancedsystems are only found on its Alaskan fleet, which due to Alaskanlaw are subject to the strictest environmental standards in the in-dustry. Royal Caribbean deems them unnecessary on cruise shipsthat travel other routes.

This example, like those outlined in the Introduction, depicts a companymaking a statement that is true, yet not the whole truth. We view this asparadigmatic of greenwash. In fact, Dont Be Fooled implicitly agrees with thisperspective. Consider its discussion of BPs "On the Street" campaign:

On the Street is only selectively honest. The ads mention BPssolar power and clean fuel initiatives, but fail to mention other im-portant initiatives. For example, during 2003, BP made an ultra-deep petroleum discovery off the coast of Angola, launched an oilproducts terminal in the expanding market of Guangdong, China,and acquired a 50% stake in Russias third-largest oil and gas busi-ness. Contrary to the focus of On the Street, BPs innovations andinvestments are by no means limited to environmental endeavors."5


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in accounting indicates that this is a common practice in corporate environ-mental disclosure.6 Note that this is not the same as having a poor record ofenvironmental performance. A firm can have a poor record without presentingany positive information about itself, or can have a relatively good record whilesimultaneously promoting its positive actions publicly and failing to discuss its(few) negative environmental impacts. Note also that greenwash is not thesame as simply failing to report negative information; greenwash involves the

additional step of selectively choosing to report positive information. These dis-tinctions will turn out to have important implications as we develop our formalmodel below.

3 Basic Model

Our model focuses on a single firm, whose stock is traded publicly, and a non-governmental organization (NGO). The firm has N different activities that have

some potential eff

ect on the environment. The magnitude of N is assumed tobe common knowledge, e.g., available on the firms web site or Annual Report,as is the non-environmental economic value of each activity. However, theenvironmental impacts of the firms portfolio of activities is not known at theoutset of the model. The environmental impacts of the firms N activitiesmake up its environmental profile. The model presented in this section drawsheavily upon the work of Shin (2003). However, Shin does not incorporate thepresence of an NGO that can audit the firms reports, an extension we introducein section 4.

There are 3 periods. Let Vt represent the expected value of thefi

rm inperiod t. At period 0, there is common knowledge about the likelihood thereis an environmental liability associated with any given product. Each activitygenerates an environmental benefit of value u (e.g., an outcome that improvesthe firms public image) with probability r, and an environmental liability ofvalue d with probability 1 r. Thus, the expected number of environmentalliabilities the firm faces is simply (1 r)N, and its market value in period 0 is

V0 = (ru + (1 r)d)N

eV , (1)

where eV is the total value created by the firm in activities that have no appre-ciable environmental impacts. Throughout the remainder of the paper, we willsimplify notation by normalizing eV to 1. At period 2, all information becomescommon knowledge, and is incorporated into stock prices. The important ac-tion in the model takes place in the interim period 1.

We assume there is a probability that the firm actually learns the envi-ronmental impact of the activity by period 1 Thus at the interim period


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the ability to disclose publicly the number of activities that demonstrably haveenvironmental benefits. We assume that all such disclosures are verifiable byoutside parties. Thus, the firm is free to selectively withhold information, butit cannot actually lie to outsiders. We assume the manager adopts a disclosurestrategy that maximizes the value of the firm. It is worth noting that we wouldexpect to be greater for firms that have created an environmental managementsystem. This is a point to which we return in section 4.

Let n be the actual number of activities whose liabilities are known at theinterim period, s be the number of successes and f the number of failures, sothat n = s + f. Let the firms disclosures of successes and failures be givenby bs and bf . Following Shin (2003), we assume the market sets the price of thefirm equal to its actuarily fair value given all available information. Hence, themarket acts as if it had an objective function to minimize (V1 V2)2, where V2is the publicly known liquidation value of the firm at the end of the game. Atthe interim period, the market minimizes the expected value of the loss functionby setting V1 = E(V2). If the market knows s and f, as would be the case if

the firm fully disclosed its information in period 1, then

V1 = E(V2) = usdf(ru + (1 r)d)Nsf, (2)

where u = the multiplicative impact of a success on the firms value and d =the multiplicative impact of a failure on the firms value. This formula is quiteintuitive, since u and d are the values of successes and failures, respectively, and(ru + (1 r)d) is the expected value of an activity whose environmental impactremains unknown.

If the firm discloses bs > 0, the NGO investigates the firms report for thepossibility of greenwash. With probability the NGO obtains hard (verifiable)information about the true values of s and f at the interim period; with prob-ability 1 it learns nothing. If it learns the true state, then it reports thisinformation publicly, and can impose a penalty P(bs, bf; s, f), where bs = numberof successes reported and bf = number of failures reported. This penalty mightcome about because the NGO triggers a consumer boycott, because it createsan advertising campaign that damages the firms value, or through some otherchannel that the firm finds costly.

We are interested in Perfect Bayesian Equilibria (PBE), which involve spec-ifying a disclosure strategy for the firm, a market valuation, and a set of beliefsfor each time t such that (a) the disclosure strategy (bs, bf) is a best responsemapping for a firm with actual environmental profile (s, f), given the marketspricing policy and the beliefs of the market and the NGO, (b) V1 = E(V2) giventhe markets beliefs at period 1 and the firms disclosure strategy, and (c) atperiod 0 the market believes the expected number of environmental liabilities


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report f = 0. The reason is that a success is more valuable than a failure, thatis, u > d, so the expected value of an activity whose environmental impact isunknown is greater than the value of a failure, that is, ru + (1r)d > d. Hence,the manager always prefers to minimize the number of failures reported, andfull disclosure is not an equilibrium strategy. Shin (2003) refers to the strategyof not disclosing any failures as sanitization. Greenwash can be thought of asa special form of sanitization that involves both a refusal to disclose failures and

the disclosure of at least one success. The distinction between sanitization andgreenwash may seem overly subtle, but it becomes important in the analysisbelow because the typical complaints about greenwash are targeted at firmsthat trumpet their successes but withhold their failures. As pointed out in theIntroduction, NGOs tend to punish greenwash specifically, not just sanitization.

Shin (2003) shows that if the manager follows the sanitization strategy inequilibrium, and the market knows this, then the firms expected value at theinterim stage is

Vsanitize = us(qu + (1 q)d)Ns, (3)

where

q =r r1 r

is the probability of success of an activity conditional on the fact that themanager has not disclosed information about that activity.7 Note that thisexpression has the same structure as equation (2), except that r (the ex anteprobability that an activity succeeds) in (2) is replaced by q (the conditionalprobability that an undisclosed activity succeeds) in (3). The sanitization equi-librium is supported by a set of off-equilibrium beliefs on the part of the marketthat if the manager ever reports f > 0, then all undisclosed outcomes are fail-ures.8

It is natural to ask whether the NGO can effectively punish greenwash with-out auditing, e.g. by penalizing the firm retroactively based on the ultimateoutcomes in period 2. It turns out this is not possible. As we noted in section2, punishing greenwash is distinct from simply punishing the firm for bad envi-ronmental outcomes. Punishing greenwash involves punishing firms that wereaware of, but failed to disclose, a failure. At period 2, however, all the NGOknows is the ultimate number of failures, NOT the number that were knownat the interim period. Thus, it is impossible to punish greenwash per se byonly observing period 2 outcomes. Instead, it is essential to have some sort ofindependent auditing structure in period 1. This is the issue to which we nowturn.

7 Recall that by Bayes Rule, the probability an undisclosed project succeeds is q =Pr(success|undisclosed) = Pr(success&undisclosed)/Pr(undisclosed) = r(1 )/(1 r).

8


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4 The Role of External Auditing

In this section we assess how auditing by an NGO affects the firms incentives tomake environmental disclosures. We derive the conditions under which NGOauditing can prevent greenwash, and then discuss an interesting complemen-tarity between the NGOs efforts and whether or not the firm has created anenvironmental management system.

4.1 The Equilibrium with Auditing by an NGO

Lets start with the simplest audit technology we can think of. If the NGOspends some amount of money A, then it gets a draw. With probability it learns the true values of s and f at the interim period. With probability1 it learns nothing. If it knows the true state, then it can impose a penaltyP(bs, bf; s, f), where bs = number of successes reported and bf = number of failuresreported. For example, the penalty might take the form of a consumer boycott

or damage to thefi

rms public image.In order to keep the analysis tractable and focused, we present it in thecontext of a model with N = 2. This is the simplest setting in which greenwashcan emerge as an equilibrium outcome. Table 1 presents the firms payoffs foreach set of possible reports the firm can make at period 1. In each box, payoffsconsist of two components, each of which is indexed by the number of successesand failures reported by the firm at period 1. The first component is the firmsmarket value as assessed by the market, and the second is the penalty imposed bythe NGO. We will use the notation (s, f) to indicate the firms full-disclosure

value, and the notation V1(bs, bf) to indicate the markets valuation of the firmwhen it makes the disclosure (bs, bf). Note that when bn bs + bf = 2 the markethas no problem inferring the firms true state, since information disclosures areverifiable. These values are easily seen to be (0, 2) = d2, (2, 0) = u2, and

(1, 1) = ud. It is only in states where bn bs + bf < 2 that we must carefullyanalyze the markets inference problem. (It is also worth noting that if thefirm faced no penalties it would always pursue the sanitization strategy; this isprecisely the case treated above in section 3.1.)

2 (0, 2)1 V1(0, 1) (1, 1)0 V1(0, 0) V1(1, 0) P(1, 0; s, f) (2, 0)bfbs 0 1 2

Table 1: Payoffs for the Firms Possible Reports (bs, bf) in period 1


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which the firms true situation really is (1, 1), as this is the only possible casewithin the case of N = 2in which greenwash can occur. Specifically, green-washing would consist of claiming to be (1, 0) when the firm is really (1, 1). Thus,

P(bs, bf; s, f) = 0 for all situations with the one exception that P(1, 0; 1, 1) > 0.We want to understand what the firm will report when (s, f) = (1, 1). There

are four reporting possibilities: (

bs,

bf) {(0, 0), (1, 0), (0, 1), (1, 1)}. Given the

arguments we have made above, however, it is intuitively clear that the firm

has no incentive to report (bs, bf) = (0, 1), so we focus on the other three casesin sequence.

In order to understand the firms reporting incentives, we must know howthe market will interpret each of the three possible reports. Consider themin turn. The probability that the firm is actually of type (1, 1) can then becomputed via Bayes Rule. Table 2 below presents the prior probability of eachtrue type at the interim period, along with the value the market attaches tothat type:

State Probability (s, f)(0, 0) (1 )2 (ru + (1 r)d)2(1, 0) 2r(1 ) u(ru + (1 r)d)(2, 0) r22 u2

(0, 1) 2(1 r)(1 ) d(ru + (1 r)d)(0, 2) (1 r)22 d2(1, 1) 2r(1 r)2 ud

Table 2: Interim Period States, Probabilities, and Values

We will use the notation (bs, bf; s, f) to indicate the probability the marketassigns to the firm playing reporting strategy (bs, bf) when it is of type (s, f).9 Inaddition, we will define(bs, bf) as the probability the market assigns to observinga report (bs, bf); this is the sum of the probabilities of each interim type of firmmultiplied by the probability that type reports (bs, bf). For example,

(0, 0) = (1 )2(0, 0|0, 0) + 2(1 r)(1 )(0, 0|0, 1)+(1 r)22(0, 0|0, 2) + 2r(1 r)2(0, 0|1, 1).

We turn now to the expected value the firm of type (1, 1) obtains fromalternative possible disclosure strategies. If the (1, 1) type reports (1, 1), themarket knows for sure the firms type, and the firm has market value

E[1, 1|1, 1] = ud. (4)

If the (1 1) type reports (1 0) then the market believes it is either a (1 0)


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knows its true type at the interim period. If the firm reports (0, 0), the marketinfers that the firm is lying, since it is almost certain that the firm knows bothrealizations of its activities. Thus, the market believes the firm must be eithera (0, 2) or a (1, 1). Since being a (1, 1) is strictly better than being a (0, 2),the firm prefers to report truthfully when it finds it is a (1, 1). As goes to0, the inequality goes to r < (

ud d)/(u d). Since u > d by definition,

the rintercept of the inequality is strictly between 0 and 1. As r goes to 0,again the inequality always holds. The reason is that it is extremely unlikelythat the firm obtains any successes at all. Hence, reporting (1, 1) is a favorablestatement relative to the markets prior expectation that the firm is a (0, 2).More generally, the firm will report truthfully when a report of (1, 1) is goodrelative to the markets prior expectation, that is, when r is small enough.

Similarly, we find that E[1, 1|1, 1] > E[1, 0|1, 1] simplifies to

P(1, 0; 1, 1) > ru (u d) (1 ) . (8)Note that without the threat of an audit and a penalty, the firm will never

report truthfully, since ru (u d) (1 ) > 0 for all r,u, > 0. We will saythat NGO auditing is weak" if P(1, 0; 1, 1) > ru (u d) and strong ifP(1, 0; 1, 1) < ru (u d) . The implications of this distinction can be seenin Figures 2 and 3, which superimpose inequality (8) onto Figure 1.

In Figure 2, NGO auditing is weak, which means that as goes to zero, therintercept of (8) lies below that of (7). The dashed curve captures the effectof NGO auditing: above this curve the firm prefers greenwash to full disclosure,while below the curve the firm prefers full disclosure to greenwash. Intuitively,

above the curve the market gives thefi

rm the benefi

t of the doubt if it doesnot disclose a failure: there is a good chance the firm is uninformed about itsenvironmental impacts ( is low), and on average the firms activities are likelyto be benign (r is high). Thus, in this region, if the firm fails to report a failure,the market believes the unreported activity is probably a success; disclosing afailure would lower the firms market value significantly, so the firm prefers togreenwash and take the risk of having a penalty imposed.11

Below the dashed curve in Figure 2, the market suspects the worst if thefirm does not disclose the outcome of the second activity: the firm is probably

informed about its environmental impacts ( is high), and on average thefi

rmsactivities are environmentally damaging (r is low). Thus, in this region, ifthe firm fails to report a failure, the market believes the unreported activityis probably a failure; disclosing a failure has little impact on the firms marketvalue, so the firm prefers to fully disclose rather than run the risk of a penalty.Nevertheless, the firm may still prefer non-disclosure to full disclosure, and thisis exactly what happens in the region above the solid curve but below the dashed


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of non-disclosure. As a result, the market receives less information about thefirm than it would otherwise have received, which reduces the accuracy of stockprices and increases market volatility. Unfortunately, as shown in the Corol-lary below, this socially undesirable outcome occurs increasingly often as theexpected penalty imposed by the NGO increases. In Figure 2, this can bepictured as a shift of the dashed curve inwards and upwards.

In Figure 3 we depict the firms disclosure strategy when NGO auditing

is strong. Relative to Figure 2, the region in which the firm greenwashes isreduced, but the non-disclosure region is expanded. Thus, there is a substantialregion in which the NGO has a negative overall effect on the marketits mainimpact is to reduce the flow of information from the firm to investors.

The following Proposition summarizes the sufficient conditions for the firm tofully disclose its environmental performance information in the interim period.

Proposition 1 When the NGO punishes greenwash by imposing the penaltyP(1, 0|1, 1), thefirm cannot be induced to fully disclose its private information.

In particular, a firm with no successful activities will always fail to disclose itsfailures. However, greenwash can be deterred (that is, afirm of type (1, 1) can

be induced to report truthfully) if (a) r

ru (u d) (1 ) .

The first condition in the Proposition simply says that the penalty for be-ing caught greenwashing must be large enough to deter the firm from reporting(1, 0) when the state is (1, 1). Even when this condition is met, however, thereis no guarantee that the firm discloses fully. In fact, it may instead retreat to

disclosing nothing at all. The second condition identifies the conditions underwhich the firm prefers to disclose fully rather than disclose nothing. The smalleris , the smaller is the set of r for which the firm elects not to greenwash, thatis, the less likely that the firm fully discloses. Also, when r is small the firm ismore likely to fully disclose. The intuition is that if the firm announces (0, 0),then the market infers the firm is likely to be either a (0, 1) or a (0, 2), neitherof which is appealing, so the firm discloses (1, 1). We summarize the conditionsfacilitating full disclosure in the following corollary to Proposition 1.

Corollary 2 Greenwash can be prevented for a larger range of parameter valueswhen (a) the probability an activity is environmentally benign is small, (b) theprobability the manager knows the environmental impact of a given project atthe interim period is large, (c) the probability an audit is informative is large,(d) the penalty imposed by the NGO on a firm that is caught greenwashing is


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the firms activities are likely to have negative environmental impacts, and thatthe firms manager is likely to know the environmental impacts of the firms ac-tions by the interim period. This case is perhaps most likely to describe firmswith well-developed environmental management systems in industries with sub-stantial environmental externalities, which we will refer to with the shorthandwell-informed firms in dirty industries. Second, the firm may decide to dis-close nothing, which occurs if r is large and/or is small. These parameter

values mean the firm is unlikely to have substantial environmental impacts, butalso unlikely to know about these impacts at the interim period. This case isperhaps most likely to describe firms with poorly developed environmental man-agement systems in industries with modest environmental externalities. We willrefer to them with the shorthand poorly informed firms in clean industries."These results imply that punishing greenwash is not necessarily beneficial forsociety, as is formalized in the following Corollary to Proposition 1.

Corollary 3 Whenever the NGO imposes a strictly positive expected punish-

ment for greenwash, there exists a set of parameter values for which the NGOsactions reduce informationflows to the market and hence are socially detrimen-tal. As the expected penalty increases, this set expands.

Proof. When condition (a) of Proposition 1 holds but (b) does not, the firmof type (1, 1) chooses to report (0, 0) instead of (1, 0), which is what it wouldreport absent the NGOs audit. This change in disclosure strategy deprives themarket of the information that the firm had a success. Since the markets goalis to minimize the difference between the expected and realized values of V2,this loss of information reduces the accuracy of the markets valuation in theinterim period, and hence reduces overall market performance, which is sociallydetrimental.

We turn now to showing that the set of parameters for which informationflows are reduced expands with the expected penalty; that is, we show that theregion between the solid and dashed lines in the upper right portion of Figure2 expands when P(1, 0; 1, 1) increases. To do so, we show two things aboutthe locus of points for which (8) holds with equality. First, we show thatd/dP(1, 0; 1, 1) < 0, and second, 2r/P(1, 0; 1, 1) > 0. The desired locusof points is defined by P(1, 0; 1, 1) = ru (u

d) (1

) . Totally differentiating

this expression, it is easy to show that d/dP(1, 0; 1, 1) = /ru(ud) < 0 andthat d2r/ddP(1, 0; 1, 1) = /u(u d)(1 )2 > 0. Thus, when the expectedpenalty increases, the dashed line in Figure 2 shifts inward and becomes flatter,thereby increasing the size of the region between it and the solid line.

Corollary 3 shows that punishing greenwash is not necessarily beneficial forsociety. There is a real possibility that NGO activity against greenwash could


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this recommendation. The firms indicted by Greer and Bruno include suchgiants of the petroleum and chemical industries as Royal Dutch/Shell, Mobil,Dow, DuPont, and Monsanto. These firms operate in industries known to havesubstantial environmental impacts, and are large and well-managed enough thatone would expect them to be well informed about environmental impacts of theiractivities. However, the targets also include Asea Brown Boveri, condemnedin part because its pressurized fluidized bed combustion (PFBC) plants for

coal emit only marginally less carbon dioxide than conventional coal-burningpower plants, even though their emissions of sulfur dioxide are 59 percent lowerand emissions of nitrogen oxides are 50 percent less than conventional plants.What would happen if ABB stopped touting its PFBC plants? Presumablythere would be less use of PFBC and more use of conventional coal-burningplants, which would lead to a dirtier environment. It is hard to see how thiscould be an environmentally favorable outcome. In addition, Heinz Corpora-tion (owner of Starkist Tuna) is condemned because even though it was the firstfirm to commit to dolphin safe tuna fishing techniques, it did not support reg-

ulation offishing practices in the Eastern Pacific, and did not contribute to aninternational research program for alternative fishing methods and equipment.Whether censuring ABB and Heinz could reasonably be expected to make themmore forthcoming or more environmentally friendly is questionable.

4.2 Environmental Management Systems and NGO Au-

diting

As noted above, NGO auditing of greenwash is not guaranteed to be socially

valuable. It is particularly likely to backfire for poorly informed firms in cleanindustries, that is, when r is large and/or is small. This observation suggeststhat there is a complementarity between the NGOs auditing activities andthe presence of environmental managements systems (EMS) within the auditedfirms, which would be interpreted in our model as increasing . In our model,however, firms have no incentive to adopt an EMS, since the firms marketvalue in the interim period is lower when it adopts an EMS, as is shown in thefollowing proposition.

Proposition 4 In the interim period, the firms value in the sanitization equi-librium is decreasing in .

Proof. Differentiating equation (3) with respect to yields dVsanitize/d =us(N s)(qu + (1 q)d)Ns1(u d)(dq/d). All terms in this expression arepositive with the possible exception ofdq/d. Recalling that q = (rr)/(1r),


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valuation of the firm reflects only the possibility, not the certainty, of a failure.However, as the likelihood increases that the firm knows the environmentaloutcomes of its activities, the market increasingly interprets non-disclosure aswithheld negative information rather than as true uncertainty on the part ofthe firm. Adopting an EMS improves the firms internal information, and thusmakes the market increasingly skeptical when the firm does not fully discloseall possible environmental information.

Admittedly, our model does not incorporate the benefi

ts of an EMS in termsof improved internal control and ability to comply with environmental regula-tions. Nevertheless, our analysis does identify a countervailing incentive thattends to deter firms from adopting EMSs. Furthermore, our story is broadlyconsistent with the empirical results of Delmas (2000), who finds that manyfirms elect not to adopt ISO 14001 (a particular form of EMS) because theywish to limit public access to internal information about their environmentalperformance.

Our results suggest that public policy pressures may be required to induce

a broad cross-section of firms to adopt EMSs. Interestingly, Coglianese andNash (2001, p. 15) find that there has been an explosion of programs in theUnited States that offer financial and regulatory incentives to firms that imple-ment EMSs." These programs are being implemented at both the federal andstate levels. Whether these programs are likely to achieve their objectives isunclear. Coglianese and Nash (2001, p. 16) point out that [a]ll of these policyinitiatives are premised on the assumption that EMSs make a difference in envi-ronmental performance. Yet this question merits research and evidence ratherthan untested optimism." Our analysis points to a different rationale for en-

couraging firms to adopt EMSs. We do not presume that an EMS makes anydifference in environmental performance, but instead simply assume an EMSimproves the firms internal information about its environmental performance.In this capacity, an EMS operates as a complement to NGO auditing of environ-mental disclosure and greenwash. With an EMS in place, when a firm disclosesnothing about its environmental performance, the market infers that the firm isfailing to disclose some negative information, and thus downgrades its rating ofthe companys value. The threat that its stock will be devalued makes a firmless willing to adopt a policy of non-disclosure. In turn, this means that an

NGOs threat to punish greenwash is more likely to drive the firm to disclosefully rather than to not disclose at all.Our analysis points to a new rationale for encouraging firms to adopt EMSs,

one that does not appear to have been recognized in prior literature, either byacademics or practitioners. In effect, the presence of the EMS brings the marketcloser to a state of common knowledge, thereby increasing market efficiency.With an EMS in place, the firm is more likely to be well informed about its own


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There are three states to investigate: (0, 1), (0, 2), and (1, 1). Firms of type(1, 0) and (2, 0) have no reason to not disclose, while type (0, 0) has no options.Note that states (0, 1) and (0, 2) were not part of our analysis in section 4,because they do not involve greenwash proper, that is, they dont involve anyreporting of positive information. We consider the three relevant states (ortypes offirm) in turn.

Type (0, 1) : If the firm is of type (0, 1), there are two possible reports:

(0, 1) or (0, 0). If thefi

rm reports (0, 1), the market assumes thefi

rm may beof types (0, 1), (0, 2), or (1, 1). However, it doesnt seem to make any sense fora (1, 1) to report (0, 1). We will assume the market places no probability onthis possibility, that is, (0, 1|1, 1) = 0. Assuming the firm reports all positivenews, then the market knows the firm can be either a type (0, 1) or (0, 2). Thus,

E[0, 1|0, 1] = d(ru+(1r)d) 2(1 r)(1 )(0, 1|0, 1)(0, 1)

+d2(1 r)22(0, 1|0, 2)

(0, 1).

Similarly,

E[0, 0|0, 1] =(1 )2(ru + (1 r)d)2 + 2(1 r)(1 )[d(ru + (1 r)d)](0, 0|0, 1)

(0, 0)

+(1 r)22d2(0, 0|0, 2) + 2r(1 r)2ud(0, 0|1, 1)

(0, 0) F(0, 0; 0, 1).

Type (0, 2): If the firm is of type (0, 2), there are three possible reports:(0, 2), (0, 1) or (0, 0). If the firm fully discloses, the firm can confirm this fact

and the firms value is

E[0, 2|0, 2] = d2.

If the firm reports (0, 1), the market assumes the firm may be of types (0, 1),(0, 2), or (1, 1). However, it doesnt seem to make any sense for a (1, 1) to report(0, 1). We will assume the market places no probability on this possibility, thatis, (0, 1|1, 1) = 0. Assuming the firm reports all positive news, then the marketknows the firm can be either a type (0, 1) or (0, 2). Thus,

E[0, 1|0, 2] = d(ru+(1r)d) 2(1 r)(1 )(0, 1|0, 1)(0, 1)

+d2 (1 r)22(0, 1|0, 2)(0, 1)

F(0, 1; 0, 2).

If the firm reports (0, 0), the market must assess what type of firm it faces,which could be (0, 0), (0, 1), (0, 2) or (1, 1). Noting that (0, 0|0, 0) = 1, we canwrite the firms expected payoff as


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Type (1, 1): If the (1, 1) type reports (1, 1), the market knows for sure thefirms type, and the firm has market value

E[1, 1|1, 1] = ud.

If the (1, 1) type reports (1, 0), then the market believes it is either a (1, 0)and revealing truthfully, a (2, 0) failing to report a success, or a (1, 1) andengaging in greenwash. The firms expected value in this case is

E[1, 0|1, 1] = u(ru + (1 r)d) 2r(1 )(1, 0|1, 0)(1, 0)

+ u2r22(1, 0|2, 0)

(1, 0)

+ud2r(1 r)2(1, 0|1, 1)

(1, 0) F(1, 0; 1, 1).

If the (1, 1) type reports (0, 0), then the market will conclude this reportmight have come from any of types (0, 0), (0, 1), (0, 2) or (1, 1).13 The firmreceives an expected payoff of

E[0, 0|1, 1] =(1 )2(ru + (1 r)d)2 + 2(1 r)(1 )d(ru + (1 r)d)(0, 0|0, 1)

(0, 0)

+(1 r)22d2(0, 0|0, 2) + 2r(1 r)2ud(0, 0|1, 1)

(0, 0) F(0, 0; 1, 1).

5.1 The Full Disclosure Equilibrium

We are interested in the conditions that will induce all types to disclose fully.In the full disclosure equilibrium, the market will assesses (s, f|s, f) = 1 and

(bs, bf|s, f) = 0 for any bs 6= s or bf 6= f. For full disclosure to be incentivecompatible, we must have

E(s, f|s, f) > E(bs, bf|s, f) bs, bf 6= s,f.The following conditions must hold in a full disclosure equilibrium

E[0, 1|0, 1] > E[0, 0|0, 1] d(ru + (1 r)d) > (ru + (1 r)d)2 F(0, 0; 0, 1).

E[0, 2|0, 2] > E[0, 1|0, 2] d2 > d(ru + (1 r)d) F(0, 1; 0, 2).E[0, 2|0, 2] > E[0, 0|0, 2] d2 > (ru + (1 r)d)2 F(0, 0; 0, 2).E[1, 1|1, 1] > E[1, 0|1, 1] ud > u(ru + (1 r)d) F(1, 0; 1, 1).


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F(0, 0; 0, 1) > F(0, 0; 0, 1) r(u d)(ru + (1 r)d)

.

F(0, 1; 0, 2) > F(0, 1; 0, 2) r(u d)d

.

F(0, 0; 0, 2) > F(0, 0; 0, 2)

r (u d) (2d + r(u d))

.

F(1, 0; 1, 1) > F(1, 0; 1, 1) r(u d)u

.

F(0, 0; 1, 1) > F(0, 0; 1, 1) (u d) (ur2 d(1 r)2)

.

The following Lemma ranks the minimum thresholds F(bs, bf|s, f), which willbe convenient in establishing results below.

Lemma 5 (a) F(1, 0; 1, 1) > F(0, 0; 0, 1) > F(0, 1; 0, 2) > F(0, 0; 1, 1) and (b)F(0, 0; 0, 2) > F(0, 0; 0, 1).

Proof. In (a), the first two inequalities are clear from inspection. Next, observe

that F(0, 1; 0, 2) > F(0, 0; 1, 1) ifrd > (ur2d(1r)2), which can be rearrangedto form r2(ud) + d(1 r) > 0. In (b), observe that F(0, 0; 0, 2) > F(0, 0; 0, 1)

if 2d + r(u d) > ru + (1 r)d, which can be rearranged to form d > 0.In light of the Lemma, the only unresolved question regarding the necessary

penalties to induce full disclosure is whether F(0, 0; 0, 2) F(1, 0; 1, 1). It iseasy to see that F(1, 0; 1, 1) > F(0, 0; 0, 2) if u > 2d + r(u d), or

r u/2, then this condition always fails. This is the case whenthere is relatively little variance associated with the environmental activity.Regardless of whether the condition holds, however, it is possible to establishsufficient conditions on penalties that will induce full disclosure, as shown in thefollowing proposition.

Proposition 6 Full disclosure can be induced through a policy of mandatorydisclosure that includes penalties at least as great as u(u d)/ for failures to


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Proof. Ifr < (u 2d)/(u d), then F(1, 0; 1, 1) > F(0, 0; 0, 2), and a sufficient

condition for full disclosure is F(1, 0; 1, 1) > r(u d)u/.If r > (u 2d)/(u d), then F(0, 0; 0, 2) > F(1, 0; 1, 1), and a sufficient

condition for full disclosure is F(0, 0; 0, 2) > (u d) (ur2 d(1 r)2)/. Sincer < 1, a penalty of F u(u d)/ is always sufficient to induce truthfuldisclosure, since F > F(0, 0; 0, 2) and F > F(1, 0; 1, 1).

The proposition shows that mandatory disclosure requirements, with therequisite level offines, are more powerful instruments than penalizing greenwashalone. As we found in section 4, full disclosure can never be achieved simplyby auditing and punishing greenwash. Furthermore, the NGOs ability to detergreenwash depends importantly on the values of parameters such as r and .Mandatory disclosure requirements offer the ability to eliminate withholding ofinformation, regardless of r or .

Although mandatory disclosure rules are attractive in principle, in practice

they may require the use offi

nes that are too large to be politically feasible.If so, then there is no guarantee that a mandatory disclosure law will be moreeffective than auditing by an NGO. We turn to this issue in the followingsection.

5.2 Limited Regulatory Penalties

In the previous section, we showed that if there are no limits on penalties forfailure to disclose information, then legislative requirements can induce com-panies to fully disclose their environmental risks. Often, however, governmentpenalties are less than would be required to prevent socially damaging corporateaction.14 Under Sarbanes-Oxley, firms may face fines of up to $5 million, andcorporate managers may face up to $1 million in fines. Unfortunately, fines ofthis magnitude are unlikely to induce truthful disclosure from firms of any sub-stantial size. To get a sense of the magnitudes required, note that Konar andCohen (1998) find that poor environmental performance significantly reducedthe intangible asset value offirms in the S&P 500, with the average intangibleliability valued at $360 million. For the average firm in the sample, the re-placement value of tangible assets was roughly $4.29 billion, so environmentalliabilities averaged approximately 8.4% of the replacement value of tangible as-sets. For purposes of calibration, then, suppose the firm has 10 activities withsignificant negative environmental impacts, and that the figure from Konar andCohen thus represents the impact of 10 failures. Suppose also that u = 1,so environmental successes provide no net benefit. Then d = 0.991. In addi-tion, suppose only 10% offirms are likely to be audited, so that = .1. Then


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The $5 million fine that can be levied under Sarbanes-Oxley is nowhere close toenough to discipline the reporting behavior of large firms.

If political constraints limit the fines that can be imposed, then the fulldisclosure equilibrium may fail to exist. In this case, it is natural to askwhether NGO auditing might complement mandatory disclosure requirements,and thereby restore the full disclosure equilibrium. We explore this question inthe remainder of this section.

From section 5, we know that depending upon parameter values, in somecases it is more difficult to induce full disclosure by a firm of type (0, 2), while inother cases it is more difficult to induce full disclosure from a firm of type (1, 1).In addition, we know from section 4 that NGO punishment of greenwash affectsonly the incentives offirms of type (1, 1). Suppose that r > (u 2d)/(u d),so F(0, 0; 0, 2) must be larger than any other penalty if full disclosure is to beinduced. Suppose also that the maximum politically feasible fine is Fmax. ThenNGO auditing will be of no additional value if

Fmax r(u d)u , (u d) (ur2

d(1

r)2)

.In this case, greenwash is already deterred by the mandatory disclosure rules,and NGO auditing provides no additional effect on behavior.

Alternatively, suppose r < (u 2d)/(u d), so F(1, 0; 1, 1) must be largerthan any other penalty if full disclosure is to be induced. IfFmax < r(ud)u/,then NGO auditing may in principle improve reporting behavior. Consider thecase where

Fmax (u

d) (ur2

d(1

r)2)

,

r(u

d)u

.If mandatory disclosure rules exist, but there is no NGO auditing, then afirm of type (0, 2) prefers to fully disclose, rather than report (0, 0), but afirm of type (1, 1) prefers to engage in greenwash and report (1, 0). However,if the mandatory disclosure rules are supplemented by NGO auditing, and ifF(1, 0; 1, 1) + P(1, 0; 1, 1) > ru(ud)/, then a firm of type (1, 1) will prefer toreport (1, 1) than to report (1, 0).

5.3 Mandatory Disclosure, NGO Auditing, and EMSGiven the magnitude of the fines needed to induce full disclosure, it is possiblethat even the combination of government-mandated fines and NGO penaltieswill fall short of the levels needed to induce full disclosure. If this is thecase, then EMSs re-emerge as a complementary tool that may enhance theeffectiveness of the other two mechanisms.


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If fines are moderate in size, matters become more complex. If Fmax >F(0, 0; 1, 1), then a firm of type (1, 1) would be deterred from reporting (0, 0)if all other types had incentives to report truthfully. However, if types (0, 1)and/or (0, 2) have incentives to report (0, 0), then F(0, 0; 1, 1) is not a sufficientlylarge fine to prevent the (1, 1) type firm from opting not to disclose. Thefirms adoption of an EMS would improve matters, reducing incentives for non-disclosure.

In general, none of the three tools discussed here is likely to be suffi

cient toinduce full disclosure of environmental liabilities by corporations. Combiningthe three offers promise for improving corporate disclosure, but a full analysisof the interplay between the three is beyond the scope of this paper.

6 Conclusions

This paper has presented what is to our knowledge the first economic analysis ofgreenwash. We defined greenwash as the selective disclosure of positive informa-

tion about a companys environmental performance, without full disclosure ofnegative information on these dimensions. We then modeled the phenomenonusing tools from the literature on financial disclosure. In our model, a non-governmental organization (NGO) can audit corporate environmental reports,and penalize firms caught engaging in greenwash. It is possible that the NGOsactions will deter greenwash, but we also identified conditions under which theywill backfire and induce the firm to avoid disclosing any environmental infor-mation at all, an outcome that is worse than greenwash. The likelihood ofthis outcome is reduced if the firm has adopted an environmental management

system (EMS), and the complementarity between EMSs and NGO auditing ofgreenwash points to a benefit from public policies that mandate the adoption ofEMSs. Indeed, our analysis points to a new rationale for encouraging firms toadopt EMSs An EMS brings the market closer to a state of common knowl-edge, thereby increasing market efficiency. With an EMS in place, the firmis better informed about its environmental impact, and the market knows thatthe firm is better informed. As a result the firm is unable to hide behind theveil of ignorance when it fails to fully disclose the impacts of its actions, and isthereby pressured to fully disclose.

We also studied mandatory disclosure policies, and found that they have thepotential to induce firms to fully disclose information about their environmentalactivities. However, the fines necessary to induce full disclosure may be so largeas to be politically unpalatable. If this is the case, then disclosure may requirethe use of a set of complementary instruments, including mandatory disclosurestandards, NGO auditing and implementation of EMSs.


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value, an accusation leveled against some firms. In this case, greenwash may di-vert scarce funds from valuable risky projects to relatively certain but low-valueprojects. A second area meriting research is empirical study of greenwash,its effects on corporate valuation, and its interaction with NGO informationcampaigns.

References

[1] Baron, David P. 2002. Competing for the Public through the News Me-dia, working paper, March 2003.

[2] Deegan, Craig and M. Deegan. 1996. Do Australian Companies ReportEnvironmental News Objectively? An Analysis of Environmental Disclo-sures by Firms Prosecuted Successfully by the Environmental ProtectionAuthority," Accounting, Auditing and Accountability Journal, 9: 50-67.

[3] Delmas, Magali A. 2000. Barriers and Incentives to the Adoption of ISO14001 by Firms in the United States," Duke Environmental Law and PolicyForum, 11: 1-38.

[4] Greer, Jed and Kenny Bruno. 1996. Greenwash: The Reality BehindCorporate Environmentalism. Penang, Malaysia: Third World Networkand New York: the Apex Press.

[5] Johnson, Geoff. 2003. Dont Be Fooled: The Ten Worst Greenwashers of2003, Boston, MA: The Green Life.

[6] Konar, Shameek and Mark A. Cohen. 1998. Does the Market ValueEnvironmental Performance?," working paper, Owen Graduate School ofManagement, Vanderbilt University.

[7] Laufer, William S. 2003. Social Accountability and Corporate Green-washing, Journal of Business Ethics, 43: 253-261.

[8] Lyon, Thomas P. and John W. Maxwell. 2004a. Astroturf: Interest GroupLobbying and Corporate Strategy, Journal of Economics and Management

Strategy, 13: 561-597.

[9] Lyon, Thomas P. and John W. Maxwell. 2004b. Corporate Environmen-talism and Public Policy. Cambridge: Cambridge University Press.

[10] Shin, Hyun Song. 2003. Disclosures and Asset Returns, Econometrica,71: 105-133.


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Figure 1: Full Disclosure vs. No Disclosure

rProbability

of Success

Full Disclosure

Report (1,1)

No Disclosure

Report (0,0)

Probability Manager is Informed


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Figure 2: Disclosure with Weak NGO Auditing

rProbability

of success

Full Disclosure

Report (1,1)

Greenwash

Report (1,0)

No Disclosure

Report (0,0)



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Figure 3: Disclosure with Strong NGO Auditing

rProbability

of success

Full Disclosure

Report (1,1)

Greenwash

Report (1,0)

No Disclosure

Report (0,0)


Documents

Lyon y Maxwell 2007